Human Factors in Artificial Intelligence
Preparation: familiarity with algorithms such as linear regression, decision trees, clustering, and neural networks; competence in probability distributions, statistical inference, and hypothesis testing; foundational knowledge of modern artificial intelligence/machine learning (AI/ML) comparable to an introductory undergraduate course; and proficiency in Python, including libraries such as NumPy, pandas, and scikit-learn.
1 course